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Research Policy 31 (2002) 73–94
Does technological learning pay off? Inter-firm differencesin technological capability-accumulation paths and operational
performance improvement
Paulo N. Figueiredo∗
Brazilian School of Public Administration of the Getulio Vargas Foundation (EBAP-FGV),
Praia de Botafogo, 190 4th floor room 426, 22.253-900 Rio de Janeiro, RJ Brazil
Received 21 September 2000; received in revised form 14 November 2000; accepted 3 January 2001
Abstract
This paper focuses on the practical implications of technological capability-accumulation paths for inter-firm differences
in operational performance improvement in the late-industrialising context. This relationship is examined over the lifetime
of two large steel firms in Brazil: USIMINAS (1956–1997) and CSN (1938–1997). The study has found that the techno-
logical capability-accumulation paths followed by the two case-study companies were diverse and have each proceeded at
differing ways and rates over time across different technological functions. The different ways and rates at which the two
companies have improved their key operational performance indicators were strongly associated with their technological
capability-accumulations paths. This paper suggests that the rate of operational performance improvement can be acceleratedif deliberate and effective efforts to accumulate and sustain capabilities for different technological functions-through the
underlying learning processes-are made within the firm. This paper also suggests that these efforts are likely to generate
financial benefits for the firm. © 2002 Elsevier Science B.V. All rights reserved.
Keywords: Technological capability-accumulation paths; Operational performance improvement; Technological learning; Late-industrialising
firm; Latecomer company literature; Technological frontier company literature
1. Introduction
Over the past two decades there was a profusion
of studies stressing the importance of ‘learning’and ‘capability’ for firms’ competitive performance.
However, there still is a misty idea of the practical
implications of firms’ efforts on learning and tech-
This paper is part of a broader research for the author’s Ph.D.
thesis approved in March 2000 at SPRU-Science and Technology
Policy Research, University of Sussex, UK.∗ Corresponding author. Tel.: +55-21-559-5742;
fax: +55-21-553-8832.
E-mail address: [email protected] (P.N. Figueiredo).
nological capability accumulation for competitive
advantage, particularly within the late-industrialising
context. Indeed, certain questions remain unanswered
in the literature. To what extent the way and the rateat which firms accumulate their technological capa-
bilities explain inter-firm differences in operational
performance improvement? What managers need to
do in order to improve firms’ competitive performance
on the basis of technological capability accumulation?
Are learning efforts likely to generate financial ben-
efits for the firm? If so, how? The focus of this paper
is how the technological capability-accumulation
paths influence inter-firm differences in operational
(and financial) performance improvement.
0048-7333/02/$ – see front matter © 2002 Elsevier Science B.V. All rights reserved.
P I I : S 0 0 4 8 - 7 3 3 3 ( 0 1 ) 0 0 1 0 6 - 8
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74 P.N. Figueiredo / Research Policy 31 (2002) 73–94
Being centred on late-industrialising firms, the
focus of analysis in this paper differs from most of
the recent studies on learning and capabilities in tech-
nological frontier firms. In these firms, innovativetechnological capabilities already exist. Latecomer
firms, however, move into a business on the basis of
technology they have acquired from other firms in
other countries. Therefore, during their start-up time
they lack even the basic technological capabilities. To
become competitive and catch up with technological
frontier firms they first have to acquire knowledge
to build up and accumulate their own technological
capabilities. In other words, they need to engage
in a process of technological ‘learning’. The term
technological ‘learning’ is usually understood in two
alternative senses.
The first sense refers to the trajectory or path along
which the accumulation of technological capability
proceeds. The way paths proceed may change over
time: technological capability may be accumulated
in different directions and at differing rates. The sec-
ond sense refers to the various processes by which
knowledge is acquired by individuals and converted
into the organisational level. In other words, the pro-
cesses by which individual learning is converted into
organisational learning.
Learning here is referred to in the second of thetwo senses outlined above. Hereafter, learning will be
understood as a process that permits the company to
accumulate technological capability over time. Tech-
nological capability is defined here as the resources
needed to generate and manage improvements in pro-
cesses and production organisation, products, equip-
ment, and engineering projects. They are accumulated
and embodied in individuals (skills, knowledge, and
experience) and organisational systems (Bell and
Pavitt, 1995).
The issues of technological capability buildingand the underlying learning processes have been
addressed in two bodies of literature. One of them is
the latecomer company literature (LCL) (e.g. Katz,
1976, 1987; Katz et al., 1978; Dahlman and Fon-
seca, 1978; Maxwell, 1981; Lall, 1987, 1992, 1994;
Bell, 1982, 1984; Bell et al., 1982, 1984; Hobday,
1995; Kim, 1995, 1997a, 1997b; Dutrénit, 1998). The
other is the technological frontier company literature
(TFCL) (e.g. Prahalad and Hamel, 1990; Pavitt, 1991;
Garvin, 1993; Iansiti and Clark, 1994; Patel and Pavitt,
1994; Pisano, 1997; Iansiti, 1998; Pavitt, 1998 among
others). Other studies in the TFCL have provided a
more conceptual approach to these issues (e.g. Argyris
and Schön, 1978; Nelson and Winter, 1982; Dosi,1988; Senge, 1990; Dosi and Marengo, 1993 among
others). Only a few studies have provided an empiri-
cal treatment to the intra-firm learning processes (e.g.
Leonard-Barton, 1990, 1992a, 1992b, 1995; Iansiti,
1998; Bessant, 1998). Although both the TFCL and
the LCL argue that firms would follow diverse paths
of technological capability accumulation associated
with different patterns of performance, a greater em-
pirical content of this notion is badly needed.
This study is concentrated on steel companies.
Technological capability development in steel produ-
cers has played a substantial role in the develop-
ment of the technology and the industry in different
countries over time. World-wide, the steel industry
is passing through a series of transformations. These
are associated with the emergence of new process
and product technologies and the demand for thinner,
lighter, and more resistant steel for a wide range of
applications: from car-making to the manufacture of
surgical instruments and implants. By focusing on
late-industrialising steel, this study extends and builds
on previous empirical studies on technological capa-
bility focusing on steel, though from different per-spectives (e.g. Dahlman and Fonseca, 1978; Maxwell,
1981, 1982; Bell et al., 1982; Viana, 1984; Lall, 1987;
Pérez and Peniche, 1987; Piccinini, 1993; Bell et al.,
1995; Shin, 1996).
Section 2 outlines the conceptual and analytical
frameworks to examine the relationship between tech-
nological capability-accumulation paths and opera-
tional performance improvement. Section 3 briefly
outlines the research design and methods. Sections 4
and 5 focus on the empirical discussion on inter-firm
differences in technological capability-accumulationpaths and their implications for inter-firm differences
in operational performance improvement. The closing
Section 6 outlines the paper conclusions.
2. Conceptual and analytical frameworks
This Section presents the frameworks for firms’
technological capability-accumulation paths and its
implications for operational performance improvement.
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As far as the framework to describe paths is con-
cerned, this study draws particularly on the frame-
works available in the LCL. The study makes use of
the term ‘technological capability’ in the sense definedin Bell and Pavitt (1993, 1995), which is in line with
earlier definitions of the term (e.g. Bell et al., 1982;
Dahlman and Westphal, 1982; Katz, 1976, 1987). In
addition, the paper uses a disaggregation of different
types of technological capability to describe paths
following the framework developed in Bell and Pavitt
(1995), adapted from Lall (1992). This framework
was modified to examine technological capabilities in
steel firms, as indicated in Table 1.
The columns set out the technological capabilities
by function; the rows, by level of difficulty. They are
measured by the type of activity expressing the levels
of technological capability, in other words, the type of
activity the company is able to do on its own at differ-
ent points in time. The framework consists of seven
levels of capability across five technological func-
tions: (i) facility user’s decision-making and control;
(ii) project engineering; (iii) process and production
organisation; (iv) product-centred; and (v) equipment.
Functions (i) and (ii) will be examined together under
the heading of ‘investments’.
In addition, the framework disaggregates ‘routine’
capability into Levels 1 and 2 for process and pro-duction organisation, product-centred, and equipment
activities: (i) the capability to operate steel facili-
ties on the basis of minimum accepted standards of
efficiency in the industry, hereafter ‘routine basic
capability’; and (ii) the capability to operate steel
facilities on the basis of international standards, or
recognised international certification, hereafter ‘rou-
tine renewed capability’. This latter draws on the
definition of ‘enabling capability’ (Leonard-Barton,
1995). As far as routine capabilities for investments
Fig. 1. The study analytical framework.
are concerned, they are disaggregated into Levels 1–4.
‘Innovative’ capabilities are disaggregated into Levels
3–7 for process and production organisation, product-
centred, and equipment activities. Innovative capabili-ties for investments are disaggregated into Levels 5–7.
This study traces the paths over as long a period as
possible throughout the companies’ lifetime. This allo-
wed the rate of accumulation to be tackled, in other
words, the number of years needed to attain each level
and type of technological capability for different tech-
nological functions. The accumulation of a level of
capability is identified when a company has achieved
the ability to do a technological activity that it had not
been able to do before. In addition, the paper takes
into account the building, accumulation, sustaining (or
weakening) of technological capability for different
technological functions, in other words, the consis-
tency of the paths.
As argued in Dosi (1985), there is a permanent
existence of asymmetries between firms in terms of
their operational performance. Firms can be generally
ranked as ‘better’ or ‘worse’ according to their dis-
tance from the technological frontier. In other words,
inter-firm differences in performance are interpreted
as an implication of different accumulation of tech-
nological capabilities (Dosi, 1985, 1988). Operational
performance improvement is a critical issue for com-panies in general. The issue seems even more critical
for latecomer companies since they start with levels
of performance far below world standards. To catch
up with international levels of performance, their rates
of performance improvement have to grow faster than
the rates of companies operating at the technologi-
cal frontier. The achievement of world competitive
performance depends on how fast they accumulate
their technological capability (Bell et al., 1982; Bell
et al., 1995). Only a few studies in the LCL have
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investigated operational performance improvement
associated with the firms’ technological capability
(e.g. Hollander, 1965; Katz et al., 1978; Dahlman
and Fonseca, 1978; Bell et al., 1982; Mlawa, 1983;Tremblay, 1994). However, systematic inter-firm
comparative analysis of the implications of the way
and the rate of technological capability-accumulation
paths for inter-differences in operational performance
improvement has been scarce in both the LCL and
TFCL. This relationship form the basic analytical
framework of this study, as represented in Fig. 1.
It should be noted that the original study from
which this paper is derived (Figueiredo, 1999) analy-
sed how the key features of learning processes influ-
ence inter-firm differences in paths of technological
capability accumulation and, in turn, in operational
performance improvement. This paper, however, con-
centrates on the relationship between the last two
issues. 1 Inter-firm differences in paths of techno-
logical capability-accumulation are understood here
as a reflection of the inter-firm differences in the
underlying learning processes.
3. Research design and methods
Central to this paper are the implications of thetechnological capability-accumulation paths for the
inter-firm differences in operational performance
improvement. The research is based on comparative
in-depth case studies. The choice for this strategy
was conditioned by the need to tackle these issues
with an adequate level of detail over the long term.
In addition, careful selection of the case studies was
crucial to tackle these issues. The selection process
went through four stages, as described in more detail
elsewhere (Figueiredo, 1999): exploratory work, pilot
1 I am grateful to one of the anonymous referees for commenting
on the issues related to the focus of this paper. Indeed, the paper
is not addressing the knowledge generation activities. However,
these activities, which are an important part of the analysis, were
tackled in detail elsewhere (Figueiredo, 1999) as the underlying
learning processes. The framework for learning in that study
identifies four distinct processes: external and internal-knowledge
acquisition, knowledge-socialisation and knowledge-codification
processes. These are analysed on the basis of four features: va-
riety, intensity, functioning, and interaction. However, this issue
is beyond the scope of this paper.
work, main field work, and during the writing pro-
cess. As a result, the study concentrated on two of
the largest flat steel companies in Brazil using similar
process technologies: Usinas Siderúrgicas de MinasGerais SA (USIMINAS) and Companhia Siderúrgica
Nacional SA (CSN).
To achieve a meaningful comparison of the techno-
logical capability-accumulation paths across the two
companies, the study drew on the framework in Table
1. Additionally, as the start-up dates and ages of the
case-study companies were different, a framework of
three common phases was created: start-up and ini-
tial absorption phase, conventional expansion phase,
and liberalisation and privatisation phase. These
frameworks were the key methodological ‘tools’ to
implement research activities such as fieldwork plan-
ning, interview guide design, use of the information
sources, organisation and analysis of the fieldwork
material, and the writing of the case studies. This
study is primarily based on empirical information
gathered from informants in different areas of two
large steel companies. Complementary information
was gathered from steel industry institutions in Brazil.
There were four sources of information within the
steel companies: open-ended interviews, casual con-
versations, direct-site observations and company’s
documentary archival records.The study involved more than 100 interviews in
both companies during the pilot study and main field-
work. The preparation for the fieldwork activities,
consisted of sending letters to the companies, logisti-
cal plan and the preparation of interview guides. A key
activity was the elaboration of the ‘research interme-
diate categories’. They were ‘intermediate’ because
their level of disaggregation was between the main
research questions and the interview questions. They
were built to clarify the ‘kinds of information’ needed
to illuminate the research questions. The way eachactivity was operationalised in the field (e.g. getting
started, doing the interviews, casual meetings, direct
site-observations, and decision to leave each company)
are outlined in detail elsewhere (Figueiredo, 1999).
The analysis of the empirical evidence started
during the fieldwork. A ‘memo-book’ was used where
‘notes for analysis’ were written on the basis of: (i) the
interview cards produced during the day; and (ii) the
notes on casual conversations and site-observations
(e.g. differences between companies, implications of
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80 P.N. Figueiredo / Research Policy 31 (2002) 73–94
interviews and findings for the research questions, in-
sights for the study conclusions). Following the main
fieldwork, the analysis of the empirical evidence con-
sisted of a systematic building of analytical tables.Each table focused on one research issue in each
case-study company across time. These tables were
accompanied by short analytical texts. As the build-
ing of tables progressed, depth and level of detail of
analysis of each variable increased.
This exercise evolved through four painstaking
stages permitting: (i) the identification of a different
evolution of the variables in each company; (ii) the
identification of relationships between variables with
an adequate level of accuracy; and (iii) the identi-
fication of the influence of the underlying learning
processes and intervening variables (e.g. external con-
ditions, leadership behaviour) on the paths. Addition-
ally, a systematic analysis of operational performance
improvement consisted of grouping and re-grouping
indicators into categories and contrasting them across
companies to highlight inter-firm differences. During
this stage, the combination of the quantitative with
the qualitative information was fruitful to interpret
the inter-firm differences. This process of analysis
permitted a reliable examination of the inter-firm dif-
ferences in the relationships between the variables to
make plausible interpretations and of the empiricalevidence.
Table 2
Differences in the rate of technological capability accumulation between USIMINAS (1962–1997) and CSN (1946–1997) a ,b,c
Capability levels Technological functions
Investments Process and production
organisation
Product-centred Equipment
USIMINAS CSN USIMINAS CSN USIMINAS CSN USIMINAS CSN
Routine
(1) Basic 10 15 10 45 10 40 10 20(2) Renewed 10 15 10 50 10 50 10 45
(3) Extra basic 10 20
(4) Pre-intermediate 25 40
Innovative
(3) Extra basic 10 45 10 40 10 15
(4) Pre-intermediate 25 50 15 45 20 40
(5) Intermediate 30 0 35 0 25 50 30 0
(6) High-intermediate 35 0 0 0 35 0 35 0
a Approximately the number of years needed to attain each level and type of capability.b Source: own elaboration based on the research.c In this case, the initial years refer to the operations start-up year.
4. Inter-firm differences in technological
capability-accumulation paths
This section compares the differences betweenUSIMINAS and CSN in the paths of technological
capability accumulation across four technological
functions: (i) investments (involving facility user’s
decision making and control and project planning and
implementation); (ii) process and production organ-
isation; (iii) product-centred; and (iv) equipment. In
the light of Table 1, this section begins by outlining
the inter-firm differences in the rates of technological
capability-accumulation, as indicated in Table 2.
In general, USIMINAS took 10 years to accumulate
Levels 1 and 2 across all four technological functions.
In parallel, USIMINAS proceeded, continuously, to
the accumulation of technological capability beyond
Level 4. Within 35 years USIMINAS had built up,
accumulated, and deepened innovative capability at
Level 5 (process and production organisation) and
Level 6 (investments, product-centred, and equip-
ment). In contrast, CSN took more than 45 years to
complete the accumulation of Levels 1 and 2 routine
capabilities, particularly for process and production
organisation and product-centred. During more than
40 years CSN did not move beyond the accumulation
of capability at Level 4, except for product-centredactivity. Inter-firm differences in the accumulation of
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capability across the four technological functions are
discussed below in more detail.
4.1. Investments capability
USIMINAS followed a path of continuous accu-
mulation of capability from Levels 1–6. Although
USIMINAS did not move into the accumulation of
Level 7, the company sought to deepen and routinise
Level 6 innovative capability. In contrast, CSN accu-
mulated investments capability at Level 4. During the
1990s both firms reduced their in-house investment
activities. USIMINAS moved into the deepening of a
strategic part of that capability (e.g. basic engineering
and overall project management). This permitted the
company to be in full control of strategic investment
activities and to increase the revenues from technical
assistance provided for other companies. The evi-
dence suggested that by the mid-1980s, CSN seemed
to aim for the accumulation of capability at Level 5.
However, during the 1990s, CSN went through a more
radical reduction in the in-house investment activities.
As a result, the company moved into a weaker posi-
tion in relation to USIMINAS as far as full control
and execution of strategic investment activities were
concerned.
4.2. Process and production organisation capability
USIMINAS moved from the accumulation of capa-
bility at Levels 1 and 2 to Level 5. However, USIM-
INAS was not so fast at accumulating capability for
processes as it was for products. Additionally, the
evidence suggested that in parallel with the accumu-
lation of innovative capabilities, USIMINAS routine
operating capability (Levels 1 and 2) was continu-
ously strengthened over time. As a result, much of
the innovative activities (e.g. ‘capacity-stretching’or integrated automation) were supported by routine
capability for process and production organisation.
These activities were also associated with the capa-
bility for equipment and investments (Level 4). In
contrast, in CSN it was not until the early-1990s that
the accumulation of Levels 1 and 2 capability was
completed. This incomplete accumulation of basic
operating capabilities must have constrained CSN’s
efforts, during the 1950–1980s period, to move into
the accumulation of capability at Levels 3–4. It was
not until the 1990s that CSN moved into the accumu-
lation of capability at Level 4.
4.3. Product-centred capability
USIMINAS began by accumulating Levels 1 and
2 routine capability. In parallel, the company moved
into the accumulation and deepening of capability up
to Level 6. As USIMINAS proceeded into the accu-
mulation of innovative capability for products, the
company continuously strengthened capability at Lev-
els 1 and 2. The evidence suggested that USIMINAS
would not have achieved such a fast rate of product
development capability (Levels 5 and 6) if routine
capability at Levels 1 and 2 had not been adequately
accumulated. In contrast, in CSN, it was not until the
1990s that the accumulation of capability at Levels
1 and 2 for products was completed. Although CSN
sought to accumulate innovative capability for prod-
ucts (Level 4 beyond), this was achieved only slowly
and inconsistently. As suggested by the research, one
of the reasons for this inconsistency of accumulation
in CSN was the absence of an adequate accumulation
of capability at Levels 1 and 2.
4.4. Equipment capability
Both USIMINAS and CSN engaged in the accu-
mulation of Level 1 routine capability for equipment.
However, USIMINAS moved into the accumulation
of innovative capability up to Level 6. In contrast,
CSN accumulated capability up to Level 4. By the
late-1980s, both firms were affected by the crisis in
Brazil’s capital goods industry. As a result, by the
early-1990s, both had reduced their in-house equip-
ment activities. However, although USIMINAS redu-
ced the scale of equipment activities in relation to the
1980s, it engaged in deepening the strategic part of its capability (e.g. equipment basic engineering, large
equipment manufacturing, and technical assistance
in revamping engineering). In addition, USIMINAS
sought to stretch Levels 1 and 2 routine equipment
capability into the early stages of car-manufacturing.
In contrast, CSN adopted a more radical reduction
in its innovative equipment activities. Therefore, by
the 1990s, CSN had moved into a weaker position
in relation to USIMINAS, as far as capability for
equipment activities was concerned.
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5. Implications for inter-firm differences in
operational performance improvement
This section focuses on the inter-firm differencesin operational performance improvement between the
two case-study companies. The analysis draws on dif-
ferent indicators of performance in the two integrated
steel plants. The study combines descriptive quanti-
tative evidence with qualitative evidence to explain
inter-firm differences in operational performance
improvement. Most of these differences are expressed
in terms of changes in the level of indicators and
their rate of improvement. The inter-firm comparison
of the performance of individual facilities [blast fur-
nace (BF) and steel shop] is structured on the basis
of time-periods in the facilities’ lifetimes rather than
phases. The reason for this is that the operational
units started at different dates within and across the
two companies. However, as mentioned earlier, the
two companies have followed different paths of tech-
nological capability accumulation during the three
phases. Therefore, the analysis here also refers to
these phases. Specific procedures for comparison are
outlined in each subsection below.
The analysis of inter-firm differences in operational
performance is based here on 10 different indicators.
For space limits other four indicators are not shownhere, although they were analysed in the original
study (Figueiredo, 1999). These indicators are or-
ganised here in three groups: (i) ironmaking process
performance (Section 5.1 below); (ii) LD steelmaking
process performance (Section 5.2); and (iii) overall
plant performance (Section 5.3).
5.1. Inter-firm differences in the ironmaking
process performance
This Section analyses the inter-firm differences inthe ironmaking process, particularly BF performance.
BF performance is normally examined on the basis
of three indicators: (i) coke rate (kg/t of pig iron); (ii)
BF productivity (t/m3 /day); and (iii) hot metal quality.
They are examined in Sections 5.1.1, 5.1.2, and 5.1.3,
respectively, followed by the role of technological
capability accumulation in influencing the inter-firm
differences in these indicators.
In order to provide a clear perspective of the evolu-
tion of these indicators, they are initially examined on
the basis of two time-periods: (i) the initial 10-year
period, covering the start-up year to the tenth year
of operation (Y 1–Y 10) approximately; and (ii) over a
longer period (Y 1 to 1989). In this way, the compar-ison will be roughly covering the start-up and initial
absorption phases. The indicators are then compared
during the 1990–1997 period. This period is related
to the liberalisation and privatisation phase. The com-
parison for coke rate and BF productivity takes into
consideration the change in the level of indicators and
the average annual rate of decline and/or increase (per-
cent/year). Although the three indicators are analysed
separately, this section interprets BF performance as
a whole, not on the basis of individual indicators. In
other words, it considers all three indicators to obtain
a meaningful inter-firm comparison.
5.1.1. Coke rate (kg/t of pig iron)
Coke rate is the amount of coke consumed per ton
of pig iron produced. It should be noted that coke is a
critical input into the BF. It represents about 70% of
the total cost of raw materials. The coke rate level can
be affected by the vintage of the technology embod-
ied in the furnace. Additionally, the coke rate can be
affected, positively or negatively, by factors such as
coal quality, refractory conditions, process activities
(e.g. manipulation of the burden preparation and dis-tribution, etc.), and external conditions (e.g. strikes,
raw materials supply, energy crisis, etc.). Coke rate
tends to increase slowly during the BF campaign. This
is the result of natural alterations in the internal re-
fractories. Although today it would be recommended
to assess the fuel rate (coke+ injected fuel rates), this
Section analyses coke rates more systematically than
fuel rates. The comparisons are outlined below.
5.1.1.1. Blast furnace 1. The USIMINAS BF 1 was
built in the late-1950s, embodying a later vintage of technology than BF 1 at CSN, which had been built
in the early-1940s. Consequently, the initial levels of
performance differed. However, the key issue here is
the rate of change from those differing initial lev-
els. The differences in coke and fuel rates decline
between USIMINAS and CSN for BF 1 are outlined in
Table 3.
It should be noted that during the 1970–1976
period, under the first energy crisis, the fuel rates in
USIMINAS declined from 561 to 479 kg or by 2.59%
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Table 3
Differences in coke and fuel rates decline between USIMINAS and CSN: blast furnace 1a
Periods Decline in the coke and
fuel rates level (kg/t)
Average annual rate of
decline (percent/year)
USIMINAS
Coke rates BF 1 (1962–1972) 731–485 −4.02
BF 1 (1962–1989) 731–446 −1.81
BF 1 (1990–1997) 489–399 −2.86
Fuel rates BF 1 (1970–1976) 561–479 −2.59
CSNb
Coke rates BF 1 (1950–1960) 820–814 −0.07
BF 1 (1950–1989) 820–565 −0.95
BF 1 (1990–1991) 523–514 −1.70
Fuel rates BF 1 (1970–1976) 674–690 +0.39
a Source: own elaboration based on the research.b The years 1946–1949 and 1992 are not being considered. As mentioned in the company’s documents, during the 1940s CSN had
irregular coal supply. This probably had adverse effects on the coke rate level. In January 1992, the furnace was shut down permanently.
annually on average. In contrast, in CSN, the fuel rate
increased from 674 to 690 kg or by 0.39% annually. 2
5.1.1.2. Blast furnace 2. Again the initial levels of
performance in USIMINAS’ 1965 vintage plant were
higher than in CSN’s 1954 vintage plant. However,
the subsequent rates of improvement differed. The
differences in coke rate decline between USIMINAS
and CSN for BF 2 are outlined in Table 4. It should
be remembered that during the 1970s both companies
were operating under the same energy crises.
5.1.1.3. Blast furnace 3. In this case, the vintages
of plant were similar, but the levels and rates of
performance improvement differed across the two
companies. The differences in coke rate decline
between USIMINAS and CSN for BF 3 are outlined in
Table 5.
USIMINAS had continuously been achieving coke
rates below 500 kg since 1972. In contrast, it was
not until 1992 that CSN began to achieve coke ratesbelow 500 kg continuously. From the companies’ age
perspective, in USIMINAS coke rates below that level
were achieved from the age of 10. In contrast, in
CSN they were achieved only from the age of 46.
2 Data related to fuel rates were obtained from: (i) USIMINAS;
Dados operacionais dos Altos Fornos, setembro 1997, the Technical
Information Centre, and interviews in the company; (ii) CSN,
Historico da Produção (Setor Aço), 1996, and interviews in the
company.
In CSN, higher rates of coke rate decline were only
achieved during the 1992–1997 period. Indeed, during
the 1980s, and particularly during the 1990s, CSN BF
3 even outperformed USIMINAS’ in the rate of coke
rate decline.
The fast rate at which coke rates have declined
in USIMINAS has permitted the company to catch
up earlier than CSN with world standards. By the
late-1970s, when USIMINAS was 16 years of age,
its coke rates were between 430–466 kg, while theaverage coke rates in Japan were 425–430 kg and
in Germany 490 kg. 3 In contrast, by the late-1970s,
when CSN was 33 years of age, its coke rates were still
between 513–643 kg. By 1988–1989, at the age of 27,
USIMINAS’ coke rate was in line with those of Japan
(around 470 kg). 4 In contrast, it was not until the early
1990s that CSN achieved internationally competitive
coke rates below 400 kg, as in the case of BF 3.
5.1.2. Blast furnace productivity (t/m3 /day)
This Section examines the inter-firm differences inBF productivity. This is defined as tonnes of pig iron
produced per m3 of the internal volume of the furnace
in a day. There are other definitions for BF produc-
tivity (e.g. useful volume), but this study follows the
definition used in the case-study companies. The inter-
firm comparisons across the three BFs are outlined
below.
3 See CEPAL (1984, p. 132).4 See Piccinini (1993, p. 405).
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Table 4
Differences in coke and fuel rates decline between USIMINAS and CSN: blast furnace 2a
Periods Decline in the coke and
fuel rates level (kg/t)
Average annual rate of
decline (percent/year)
USIMINASb
Coke rates BF 2 (1965–1974) 612–468 −2.93
BF 2 (1965–1989) 612–446 −1.31
BF 2 (1990–1997) 491–397 −2.99
Fuel rates BF 2 (1970–1974) 571–511 −2.73
BF 2 (1970–1978) 571–479 −2.17
BF 2 (1980–1989) 486–446 −0.95
BF 2 (1991–1997) 486–500 +0.47
CSNc
Coke rates BF 2 (1954–1964) 809–657 −2.06
BF 2 (1954–1989) 809–562 −1.03
BF 2 (1990–1997) 542–412−
3.8Fuel rates BF 2 (1970–1974) 612–598 −0.57
BF 2 (1970–1976) 612–629 +0.45
BF 2 (1982–1989) 553–562 +0.23
BF 2 (1991–1997) 494–523 +0.95
a Source: own elaboration based on the research.b The furnace was shut down for revamping during the 1975–1977 period.c The furnace was shut down for revamping and reconstruction during the 1977–1981 period.
Table 5
Differences in coke and fuel rates decline between USIMINAS and CSN: blast furnace 3a ,b
Periods Decline in the coke and
fuel rates level (kg/t)
Average annual rate of
decline (percent/year)
USIMINAS
Coke rates BF 3 (1975–1979) 486–466 −1.04
BF 3 (1975–1989) 486–491 +0.07
BF 3 (1980–1989) 529–491 −0.82
BF 3 (1990–1997) 492–407 −2.67
Fuel rates BF 3 (1975–79) 519–508 −0.53
BF 3 (1975–1989) 519–491 −0.39
BF 3 (1980–1989) 533–491 −0.90
BF 3 (1995–1997) 511–510 −0.09
CSN
Coke rates BF 3 (1977–1979) 509–513 +0.39
BF 3 (1977–1989) 509–475 −0.57
BF 3 (1980–1989) 499–475 −0.54
BF 3 (1990–1997) 492–386 −3.4
Fuel rates BF 3 (1977–1979) 509–520 +1.07
BF 3 (1977–1989) 509–496 −0.21
BF 3 (1980–1989) 500–496 −0.08
BF 3 (1995–1997) 489–508 +1.92
a Source: own elaboration based on the research.b For a meaningful comparison, and since the furnaces started in December 1974 in USIMINAS and in May 1976 in CSN, their start-up
years are not considered.
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Table 6
Differences in BF productivity increase between USIMINAS and
CSN: blast furnace 1a
Periods Increase in the
productivity
level (t/m3 /day)
Average annual
rate of increase
(percent/year)
USIMINAS
BF 1 (1962–1972) 0.57–1.45 +9.78
BF 1 (1962–1989) 0.57–2.47 +5.58
BF 1 (1990–1997) 1.9–2.24 +2.38
CSNb
BF 1 (1950–1960) 0.79–0.87 +0.96
BF 1 (1950–1989) 0.79–1.36 +1.40
BF 1 (1990–1991) 1.33–1.30 −2.25
a Source: own elaboration based on the research.b In January 1992 the furnace was shut down permanently.
5.1.2.1. Blast furnace 1. The differences in produc-
tivity increase between USIMINAS and CSN for BF
1 are outlined in Table 6. It should be noted that dur-
ing the 1946–1956 period, CSN’s BF 1 went through
three campaigns. In January 1949, its first campaign
was interrupted by a crack in the crucible. In October
1949, its second campaign was again interrupted
and by a similar problem. Its third campaign (1949–
1955) was limited by problems in the top and in the
crucible. 5 USIMINAS’ BF 1 went through one cam-
paign within the initial 9-year period 1962–1971, 6
without the frequent stoppages that took place in
CSN. These stoppages in CSN, which may reflect
inadequate process and production organisation and
equipment capabilities, clearly had negative implica-
tions for BF productivity.
5.1.2.2. Blast furnace 2. The differences in produc-
tivity increase between USIMINAS and CSN for BF 2
are outlined in Table 7. In USIMINAS over the 24-year
period 1965–1989, productivity increased from 0.77
to 2.47 t/m3 /day or by 4.97% annually on average. Incontrast, in CSN during the 35-year period 1954–1989,
productivity increased from 0.59 to 0.94 t/m3 /day or
by only 1.34% annually, more than three times less
than the rate of improvement in USIMINAS. It should
be remembered that these periods were equivalent to
the start-up and conventional expansion phases in both
5 See CSN, Historico da produção do Setor Aço, 1996, op. cit.6 See USIMINAS, Dados operacionais dos Altos Fornos, 1997,
op. cit.
Table 7
Differences in BF productivity increase between USIMINAS and
CSN: blast furnace 2a
Periods Increase in the
productivity
level (t/m3 /day)
Average annual
rate of increase
(percent/year)
USIMINAS
BF 2 (1965–1974)b 0.77–1.41 +6.95
BF 2 (1965–1989) 0.77–2.47 +4.97
BF 2 (1990–1997) 1.81–2.30 +3.48
CSN
BF 2 (1954–1964) 0.59–0.87 +3.96
BF 2 (1954–1989) 0.59–0.94 +1.34
BF 2 (1990–1997) 0.97–2.46 +14.21
a Source: own elaboration based on the research.b Shut down for revamping between 1975 and 1977.
companies. In addition, during the 1990–1997 period,
CSN BF 2 substantially outperformed USIMINAS’ in
the rate of productivity increase.
5.1.2.3. Blast furnace 3. The differences in produc-
tivity increase between USIMINAS and CSN for BF
3, a similar vintage plant, are outlined in Table 8.
Performance of BF 3 is compared here under sim-
ilar time periods. In USIMINAS during the 4-year
initial period 1975–1979 productivity increased from
1.60 to 1.79 t/m3 /day or by 2.84% annually. In CSN,
during the initial 1977–1979 period productivity
dramatically increased from 1.29 to 1.58 t/m3 /day or
Table 8
Differences in BF productivity increase between USIMINAS and
CSN: blast furnace 3a ,b
Periods Increase in the
productivity
level (t/m3 /day)
Average annual
rate of increase
(percent/year)
USIMINAS
BF 3 (1975–1979) 1.60–1.79+
2.84BF 3 (1975–1989) 1.60–2.56 +3.41
BF 3 (1980–1989) 1.69–2.56 +4.72
BF 3 (1990–1997) 2.12–2.47 +2.20
CSN
BF 3 (1977–1979) 1.29–1.58 +10.67
BF 3 (1977–1989) 1.29–1.61 +1.86
BF 3 (1980–1989) 1.74–1.61 −0.85
BF 3 (1990–1997) 1.61–2.38 +5.74
a Source: own elaboration based on the research.b Again, for a meaningful comparison, the start-up year of the
two furnaces are not considered.
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86 P.N. Figueiredo / Research Policy 31 (2002) 73–94
by 10.67% annually on average. Despite this substan-
tial rate of increase, the level of productivity of the
similar vintage plant in the 1970s in CSN was still
inferior to USIMINAS’.During the 1990s in USIMINAS productivity
increased from 2.12 to 2.47 t/m3 /day or by 2.20% on
average. In CSN, it was not until 1993 that the fur-
nace began to achieve productivity above 2 t/m3 /day.
Productivity in BF 3 increased from 1.61 in 1990
to 2.38 t/m3 /day in 1997, or by 5.74% on average.
Although in the 1990s CSN BF 3 achieved this high
rate of increase, CSN could still not catch up with the
level of USIMINAS (2.47 t/m3 /day). In CSN, as was
the case in BF 1, BF 3 suffered from sudden stop-
pages and unstable production operations, particularly
during the 1980s. Indeed, 1997 was the first year, it
operated continuously. This might have been associ-
ated with difficulties in stabilising its operations, and
significantly influenced the decline in productivity
during the 1980s.
By the late-1970s, at the age of 17, USIMI-
NAS had achieved BF productivity of 1.8 t/m3 /day,
while the average productivity in Japan in 1981 was
1.9 t/m3 /day. 7 By that time, at the age of 33, CSN had
achieved BF productivity of only 1.0 t/m3 /day. From
the companies’ age perspective, USIMINAS began
to operate with BF productivity above 1.5 t/m3 /dayfrom the age of 10. In contrast, CSN began to oper-
ate continuously with productivity above 1.5 t/m3 /day
only from the age of 41. By 1991 BF productivity
in the 29-year-old USIMINAS was 2.35 t/m3 /day on
average, while in the Japanese Kiaitsu average produc-
tivity was 2.28 t/m3 /day in that same year. 8 In 1991,
average BF productivity in Japan was 2.03 t/m3 /day.
In June 1994, USIMINAS achieved a world record
of 2.71 t/m3 /day. In contrast, in 1991, the 45-year-old
CSN had achieved average BF productivity around
1.5 t/m
3
/day. The evidence suggests that USIMINAShad been able to achieve and sustain internationally
competitive levels of BF productivity over time. In
contrast, CSN did not achieve world standards until
1992. Therefore, USIMINAS was faster than CSN in
achieving substantial improvements in BFs produc-
tivity and sustaining them at rising world competitive
levels over time.
7 For data on the Japanese mills see Gupta et al. (1995).8 See Gupta et al. (1995).
Table 9
Differences in silicon (Si) content in the pig iron between USIM-
INAS and CSNa
Periods Silicon content in the pig iron (%): average
USIMINAS CSN
1962–1969 0.89 N.A.
1970s 0.67 0.80
1980s 0.52 0.80
1990–1997 0.41 0.45
a Source: USIMINAS and CSN.
5.1.3. Hot metal quality
This Section examines the inter-firm differences in
the hot metal quality on the basis of silicon (Si) content
(%) in the pig iron. The Si content is associated with
the consumption of fuel in the BF. Reduction in Si
content is associated with the operational stability of
the BF which, in turn, is associated with the good
quality of the metallic charge. High hot metal silicon
levels have an adverse influence on BF productivity,
flux use, and also steelmaking process yield. Thus,
steel mills seek to reduce Si content. The assessment
of hot metal quality may also include the sulphur (S)
and phosphorous (P) contents in pig iron, but these
are not explored in this study. The differences between
USIMINAS and CSN are summarised in Table 9.It should be remembered that by the late-1970s both
companies were operating under the second world
energy crisis. This put pressure on energy consump-
tion world-wide, reflected in the Si content. However,
the evidence suggests that the Si content declined in
USIMINAS but remained unchanged in CSN.
In sum, during the lifetime of the three BFs USIMI-
NAS was able to combine a fast rate of decline in coke
rate (except in BF 3) with a fast rate of increase in pro-
ductivity and fast rate of decline in Si content. These
achievements certainly had positive implications forother indicators (e.g. overall energy consumption). In
contrast, in CSN, particularly during the 1950s–1980s
period, the BFs experienced slow rates of coke rate
decline (except for BF 3), a slow rate of productiv-
ity increase, and a slow rate of Si content decline.
This must have had negative implications for overall
energy consumption and steelmaking process yield in
CSN. It was not until the 1990s, and particularly from
1992 that BFs performance improved substantially in
CSN. Indeed, in the 1990s CSN even outperformed
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P.N. Figueiredo / Research Policy 31 (2002) 73–94 87
USIMINAS in terms of the rate of coke rate decline in
BF 2 and 3, and productivity increase in BF 2. How-
ever, over the long term, and on the basis of the three
indicators (including fuel rates), USIMINAS had asubstantially better overall BF performance than CSN.
Those indicators can be affected by a number of
factors, which may even obscure the role of tech-
nological capability. For instance, they can be influ-
enced by the vintage of plant, the conditions of the
refractories, the quality of the raw materials (coal),
the supply of raw materials (local or foreign), energy
crises, strikes among others. The coke consumption
may also be reduced through the use of the Pulverised
Coal Injection (PCI) technology or use of imported
coal. Even so, the role of technological capability can
be explored.
The evidence suggests that the period during which
CSN did not accumulate adequate in-house techno-
logical capability for process and production organ-
isation, particularly at Levels 1 and 2 (1940–1980s),
was associated with slow rate of performance im-
provement in the ironmaking process performance.
However, the period in which CSN began to accumu-
late Levels 1 and 2 routine and then Levels to 3–4
innovative capabilities for process and production
organisation (from the early-1990s) was associated
with better performance improvement. USIMINAS,however, had achieved competitive performance ear-
lier and more continuously over its lifetime. In sum,
USIMINAS’ experience suggests that CSN could have
achieved better performance over the 1950–1980s
period if the company had accumulated adequate
in-house technological capability.
5.2. Inter-firm differences in the LD steelmaking
process performance
This Section analyses the inter-firm differences inthe LD steelmaking process performance in USIMI-
NAS (1963–1997) and CSN (1977–1997). In USIM-
INAS there are Steel Shops 1 and 2. In CSN, it is
considered as one Steel Shop, but this Section exam-
ines the performance of the Steel Shop as a whole.
The comparison is based on periods over the lifetime
of the plants. They cover the periods 1963–1976,
1977–1989, and 1990–1997 for USIMINAS, and
1977–1989 and 1990–1997 for CSN. This is to make
the comparison more meaningful.
One initial comment is important at this stage: the
levels of the performance indicators used here are
much less determined by the level of technology em-
bodied in the vintage of plant. Indeed, the level of theindicators is more influenced by the daily operational
practices—technical and organisational -in the Steel
Shop. This Section reviews three key indicators of
the LD steelmaking process: ‘tap-to-tap’ or heat time
(min); 9 re-blow rate (%); 10 and hit rate (%) or rate
of simultaneous achievement of carbon and tempera-
ture. 11 Since they are inter-related, the indicators are
analysed together.
5.2.1. Differences in the LD steelmaking process
performance between USIMINAS (1963–1997)
and CSN (1977–1997)
The inter-firm differences across the indicators are
summarised in Table 10. In USIMINAS, the improve-
ments over time in the tap-to-tap and re-blow rates
during the 1963–1997 period may reflect the increase
in the hit rate from 36 to 85–90% during that period.
The evidence from USIMINAS indicates a substantial
performance improvement across the three indicators
during the lifetime of the Steel Shop. Although data
on hit rates in CSN is not available, the evidence on
tap-to-tap and re-blow rates suggest that its hit rates
would be much lower than in USIMINAS over thelifetime of the Steel Shop. Considering the average
ratio of the levels of re-blow rates in USIMINAS and
CSN for the 1990–1997 period, the rates in CSN were
2.7 times higher than in USIMINAS. This implies that
CSN must have accumulated higher production costs
9 The elapsed time, in minutes, between the heats in the LD
converter.10 The proportion of heats that needs to be re-blown by oxygen
for correction in the steel composition and/or temperature. In aSteel Shop, following the analysis of the molten steel samples
from the LD converter, it is decided whether to tap the heat or
to make corrections. If corrections are needed, they can be made
(a) through oxygen re-blowing; (b) through the addition of metals
(e.g. manganese) preceded by cooling procedures.11 The proportion of heats in which the steel composition
(carbon) and temperature, desired by the heat order, is simulta-
neously achieved at the heat end-point. A critical task for any
oxygen-based Steel Shop is to achieve high hit rates to prevent
time-consuming and costly oxygen re-blows or cooling procedures.
These add costly minutes to the heat time reducing the potential
productivity of the process.
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88 P.N. Figueiredo / Research Policy 31 (2002) 73–94
Table 10
Differences between USIMINAS and CSN in key steel making
process indicatorsa
Companies Tap-to-tap
(min)
Re-blow
rate (%)
Hit rate
(%)
USIMINAS
USI (1963–1976) 45–40 25–20 36–48
USI (1977–1989) 40–32 20–10 48–85
USI (1990–1997) 32 10–6 85–90
CSN
CSN (1978–1989) 62.3–38.4 36–25 N.A
CSN (1990–1997) 35–34 25–16.7b N.A.
a Sources: USIMINAS, ‘USIMINAS 25 anos’, Metalurgia
ABM, 1987, op. cit. USIMINAS [Aciaria: controle dinâmico de
fim de sopro com sublança (undated)]. Interviews in the company.
CSN, Historico da Produção: Setor Aço, 1996; ‘CSN atinge a
marca historica dos 100 milhões’, Metalurgia & Materiais, 1997,op. cit. Interviews in the company.
b Up to May 1997.
than in USIMINAS as a result of greater use of oxy-
gen, fluxes, and coolants associated with re-blows.
As mentioned earlier in the paper, Si content in the
pig iron also has an adverse influence on the steel-
making process yield. While USIMINAS entered into
the 1990s with a Si content of 0.36–0.40%, CSN’s
averaged 0.60%. This suggests that USIMINAS ente-
red into the 1990s with higher yield in the steelmak-
ing process than CSN. Additionally, in USIMINAS
the consumption of the refractories (kg/t of molten
steel) in Steel Shop 2 in 1989 was 1.9 kg/t of steel.
By 1993, it had declined to 0.69 kg/t and 0.65 kg/t in
1994. In contrast, in CSN in 1989 consumption was
9 kg/t of steel. By 1993, this had declined to only
7.3 kg/t of steel. This was the lowest level of refrac-
tories consumption CSN ever achieved, but it was
still more than 10 times higher than in USIMINAS.
These differences had positive implications for the
cost of steel produced in USIMINAS and a negative
influence on steelmaking costs in CSN.It should be remembered that during the initial
4-year period 1963–1967, USIMINAS controlled
the process parameters manually. During 1968–1975
period that control was based on the ‘catch-carbon’
strategy. 12 Nevertheless, several technical and
12 ‘Catch-carbon’ is an operational procedure whereby the desired
level of carbon is achieved by blowing oxygen to oxidise the
carbon during the steelmaking process. As a result, it brings the
carbon down to the desired level, say, 0.4% when it is ‘caught’.
production organisation modifications contributed to
improving the process parameters. Drawing on Levels
3 and 4 investment capabilities to search and select
technologies, USIMINAS introduced in 1976 the‘static charge control’. 13 This was in operation un-
til 1982. Drawing on Level 4 innovative capability,
USIMINAS developed in-house (by the Automa-
tion Unit, the Research Centre, and the Steel Shop)
mathematical models for this control system. This
contributed to the rapid decline in the tap-to-tap and
re-blow rates in the first year of the introduction of
this automated process control system.
The improvements over time in the strategies for
process control, reflect USIMINAS’ Levels 4 and
5 innovative capability for process and production
organisation. They also reflect USIMINAS’ Levels
5 and 6 innovative capabilities for investments. The
achievement of low consumption of refractories in
USIMINAS was associated with efforts to increase
the lifetime of the refractory lining of the converters.
These are associated with techniques for preventive
and/or corrective maintenance and improvements
in the operating conditions, among others. In other
words, they reflect the accumulation of capability for
equipment and process and production organisation.
The evidence from CSN suggests that these techniques
had not been developed. In contrast, by the 1990s,USIMINAS had been providing technical assistance
in steelmaking process control across Latin America.
The evidence suggests that the slow rate of improve-
ment in the steelmaking performance in CSN during
the 1970 to early 1990s period was associated with:
(i) lack of organisational units to develop in-house
process control systems and mathematical models;
(ii) poor interaction between the Steel Shop and the
Research Centre for process problem-solving; and
(iii) the long time taken to improve the daily produc-
tion organisation practices in the Steel Shop, althoughit was technically assisted during 1985–1989 period.
In other words, USIMINAS’ experience suggests that
a more effective steelmaking process control could
have been achieved earlier in CSN if the company
13 The ‘static charge control’ strategy is based on statistical,
predictive–adaptive control from static models. This control seeks
to prescribe the adequate combination of the charge materials (e.g.
hot metal, scrap, fluxes, and oxygen) required to meet the endpoint
conditions.
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P.N. Figueiredo / Research Policy 31 (2002) 73–94 89
had accumulated Levels 1–4 capability for process
and production organisation during the 1970–1980s.
5.3. Inter-firm differences in overall plant performance
This Section examines the inter-firm differences in
overall plant performance in USIMINAS and CSN on
the basis of four additional indicators.
5.3.1. Overall energy consumption (Mcal/t of steel)
This refers to the overall energy consumption in the
plant in relation to tonnes of steel produced. The dif-
ferences between USIMINAS and CSN are outlined
in Table 11. During the whole period in USIMINASthe indicator was stabilised around 6.200 Mcal/t. In
contrast, in CSN it varied more frequently reaching
the peak of 7.684 Mcal/t in 1984. In CSN, the con-
sumption in 1979 was considered a ‘record’ in the
company. Although data for the previous period is
not available, this suggests that consumption would
be higher. The stable trajectory of the indicator in
USIMINAS suggests that the company had a more
effective energy performance than CSN over time. 14
Differences in overall energy consumption (Mcal/t)
clearly reflects the fast accumulation of higher levels
of capability for process control in USIMINAS in con-trast to CSN. For instance, by the mid-1980s, USIM-
INAS engaged in efforts to build the Energy Centre
within the plant. This organisational unit sought to
improve the energy performance of the company. It
should be noted that a large part of the structuring of
that unit was done by USIMINAS independently. The
evidence from CSN suggests that systematic in-house
efforts for energy efficiency improvement over the
1970–1980s were limited. It was not until the 1990s
that the company engaged in more effective efforts to
reduce energy consumption.The evidence in this Section suggests that the more
effective performance of USIMINAS in relation to
CSN in overall energy consumption reflects their
differences in ironmaking and steelmaking processes
performance, as examined earlier. In addition, differ-
ences in the overall energy performance would have
14 USIMINAS’ more effective overall energy performance in
relation to Companhia Siderurgica Paulista (COSIPA) during the
1977–1991 period was analysed in Piccinini (1993).
Table 11
Differences in overall energy consumption (Mcal/t steel) between
USIMINAS (1977–1997) and CSN (1979–1998)a ,b
Year USIMINAS CSN Difference(CSN in relation
to USIMINAS) (%)
1977 6319 N.A –
1978 6222 N.A. –
1979 6371 7264 +14
1980 6461 6582 +1.8
1981 6851 6458 −5.7
1982 6453 7092 +9.9
1983 6225 6870 +10.3
1984 6105 7684 +25.8
1985 6069 7085 +16.7
1986 6349 6944 +9.3
1987 6206 6757 +8.8
1988 5764 7138 +23.8
1989 5646 7446 +31.8
Average annual
rate of decline
(%): 1979–1989
−1.20 +0.25
1990 6144 7584 +23.4
1991 5927 7360 +24.1
1992 6071 6756 +11.2
1993 6073 6752 +11.1
1994 6045 6749 +11.6
1995 6138 6944 +13.1
1996 6153 6863 +11.5
1997 6273 6634 +5.7
1998 N.A. 6696 –
Average annual
rate of decline
(%): 1990s
+0.29 −1.54
a Sources: USIMINAS, interview with a manager in the Energy
and Utilities Unit (Energy Centre); Technical Information Centre;
annual reports (1976–1990). CSN, interview with the adviser to
the director of the steel sector; annual reports (1975–1993).b Data for USIMINAS was provided as Mcal/t of crude steel
and for CSN as Mcal/t of molten steel. Since production volume
expressed in the latter form is slightly higher than the former, this
difference would be reflected in the data for CSN.
had greater positive implications for operating cost
reduction in USIMINAS than in CSN.
5.3.2. Labour productivity (t/man/year)
This refers to the number of operational employ-
ees in relation to the tonnes of steel produced in a
year. The evolution of the indicator is summarised
in Table 12. By the late-1980s, at 26 years of age,
USIMINAS had achieved labour productivity of
347 t/man/year, therefore, catching up with, and even
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Table 12
Comparative evolution of labour productivity in USIMINAS and
CSNa
Companies Periods Evolution of
labour productivity
(t/man/year)
USIMINAS 1963–1970 15–164
1971–1980 185–263
1981–1989 182–382
1990–1997 300–524
CSN 1950–1970 32–75
1972–1980 73–83
1982–1989 97–155
1990–1997 160–542
a Sources: companies’ annual reports.
overcoming, indicators achieved in France (386), US(429), Japan (351), and Germany (316). 15 In con-
trast, CSN by the late-1980s was 43 years of age and
had achieved productivity of 155 t/man/year. How-
ever, it was not until 1996 that CSN achieved produc-
tivity of 406 t/man/year. By 1996, USIMINAS had
achieved labour productivity of 492 t/man/year. Dur-
ing the 1990s, both companies reduced their number
of employees thereby contributing to increasing the
indicator level. For instance, during the 1990–1996
period USIMINAS reduced its number of employees
from 13 413 to 9210 or by 31.3%. During that sameperiod, CSN reduced its number of employees from
18 222 to 11 086, or by 39.1%. 16
From 1996 to 1997, the number of employees in
USIMINAS reduced from 9210 to 8359 or by 9.7%.
Interviews in CSN suggested that particularly from
1996, the company adopted a more radical approach
to the reduction of its employees: from 11 086 in
1996 to 9059 in 1997, or by 18.2%. CSN’s approach
to reductions in the number of employees did not
seem to consider the loss of qualified and experienced
individuals, in other words, the implications for the
company of the loss of tacit knowledge.
5.3.3. Number of patents
During the initial 20-year period 1962–1982,
USIMINAS had accumulated 83 patents, while
15 See ’The Brazilian Steel Institute, 1989. See also M.Sc. disser-
tation in Peixoto (1990).16 USIMINAS: annual reports, 1990–1996; Technical Information
Centre; CSN: annual reports; ‘Average operational productivity
1989–1997’ (one page, undated).
CSN had accumulated only one. During the 14-year
period 1983-1997, USIMINAS had accumulated 250
patents, with 23 overseas across 18 different coun-
tries. In contrast, during the 1983–1997 period, CSNhad accumulated 46 patents in Brazil only. These dif-
ferences reflect the differences in intensity and variety
in the original improvements to production process
control, equipment, products, and engineering across
the plant. They may also reflect the inter-firm differ-
ences in efforts on the underlying knowledge-sharing
and knowledge-codification processes, as analysed in
detail elsewhere (Figueiredo, 1999).
5.3.4. Number of product quality certificates
During the 27-year period 1962–1989, USIMINAS
accumulated 15 product quality certificates. In con-
trast, no certificate had been accumulated in CSN
during the 45-year 1946–1991 period. During the
1990–1997 period, USIMINAS obtained 26 new
certificates leading to the total of 41 certificates
accumulated over its lifetime. In contrast, it was not
until 1992 that CSN achieved its first certificate.
During the 1992–1997 period, only seven certifi-
cates were accumulated over the company’s lifetime.
The number of certificates in USIMINAS during the
early years reflects the continuous improvements in
in-house quality systems. In other words, it reflectsthe accumulation and strengthening of Levels 1 and 2
capability for products and processes and production
organisation. In CSN, the absence of quality certifi-
cates in the 1940–1980s period reflects the incom-
plete accumulation of those types of capability during
that period. However, the award of seven certificates
during the 1990s for CSN reflects the improvements
across its production lines as a result of the TQM
programme.
The evidence suggests that the achievements of
competitive product-related performance (e.g. numberof product quality certificates) in USIMINAS were
strongly associated with the accumulation of product
capability at Levels 1 and 2 and Levels 3–4 within
10 years (e.g. continuous upgrading of its quality
systems). In CSN, the improvement in the number of
quality certificates during the 1990s was strongly asso-
ciated with the completion of accumulation of Levels
1 and 2 and also innovative Levels 3–4 capability
for products (e.g. the TQM programme and efforts to
improve product quality control in the rolling mills).
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P.N. Figueiredo / Research Policy 31 (2002) 73–94 91
Table 13
Operational income margin (%)a in USIMINAS and CSN during the 1982–1990 periodb
Companies 1982 1983 1984 1985 1986 1987 1988 1989 1990
USIMINAS (1.0) 8.5 19.9 23.2 9.7 13.0 8.0 31.8 19.7CSN (14) (25) (9) (2.5) N.A. N.A. (44.1) (2.5) (78.1)
a Operating income/net sales. Numbers in brackets mean negative OIM; N.A.: not available.b Sources: USIMINAS, annual reports (1982–1990); CSN, annual reports (1982–1990).
Table 14
Key financial differences between USIMINAS and CSN in their privatisation processesa
Details USIMINASb CSNc Ratio USIMINAS/CSN
Sale proceeds (US$ million)d 1941 1495 1.29
Installed capacity in the year of privatisation (million tonnes) 4.2e 4.6f 0.91
Crude steel production volume in the year of privatisation (million tonnes) 4.1 4.3 0.95Sale proceeds/installed capacity (US$ million) 462 325 1.42
Sale proceeds/crude steel production volume (US$ million) 473 347 1.36
a Sources: BNDES (1994, 1999), USIMINAS (annual reports 1990–1991 and the Technical Information Centre); CSN (annual reports,
1992–1994).b Privatised in April 1991. The second phase of the privatisation process was completed in September 1994.c Privatised in October 1993.d It should be noted that during the main privatisation auction (April 1991), USIMINAS was sold at a price 14.3% higher than the
minimum price fixed by BNDES. In contrast, CSN was sold at the minimum price.e That refers to the ‘stretched’ capacity. The nominal capacity was 3.5 million tonnes/year.f That refers also to nominal capacity.
However, these improvements took place in CSNmuch later than in USIMINAS. Nevertheless, during
the 1990s, CSN showed substantial improvements
across a number of indicators, which were associated
with the accumulation of levels of technological capa-
bility that the company had not accumulated before.
5.4. Some implications for inter-firm differences in
financial performance
Although this study did not explore improvements
in production costs, it suggests that differences insome indicators of operational performance could have
affected production costs differently in USIMINAS
and CSN. These effects may have been reflected in
the operating income margin (OIM) of these compa-
nies. 17 For instance, during the 1980s, USIMINAS
went through a sequence of positive OIMs. In con-
trast, during this same period, CSN went through a
17 Operating income margin = operating income/net sales.
sequence of 8 years of negative OIMs, as indicated inTable 13.
As pointed out in the annual report of CSN for
1990, the company had an average negative OIM
equivalent to US$ 314 million/year during the 8-year
period 1982–1990. In contrast, as indicated in Table
13, USIMINAS experienced more effective financial
performance during that period. By the 1980s, USIM-
INAS had consolidated its leading position in terms
of financial performance among the state-owned steel
companies in Brazil. It was not until 1991 that CSN
engaged in continuous achievement of positive OIMs.Over the 1990s, USIMINAS continued achieving
positive OIMs.
The inter-firm differences in operational perfor-
mance improvement also seem to have been reflected
in the final prices at which the two companies were
sold in their privatisation processes. USIMINAS was
privatised in October 1991 and CSN in April 1993. On
the basis of data from the National Bank for Economic
and Social Development (BNDES), the organisation
responsible for the privatisation programme in Brazil,
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92 P.N. Figueiredo / Research Policy 31 (2002) 73–94
the proceeds from the sale of USIMINAS were US$
1.941 billion and of CSN were US$ 1.495 billion. 18
Table 14 outlines the key financial differences between
the two companies in their privatisation process.As indicated in Table 14, USIMINAS’ assets were
given a market value nearly 45% higher (US$ 462
million/t of installed capacity) than CSN’s assets
(US$ 325 million/t of installed capacity). It is rea-
sonable to consider that a large part of this difference
reflected the greater knowledge that was embodied
in USIMINAS’ physical, human and organisational
capital. In a similar vein, one might reasonably argue
that if CSN had accumulated knowledge as effec-
tively as USIMINAS over preceding decades, and had
embodied it effectively in physical capital, people,
organisation and procedures, it might have increased
the market value of its assets by as much as US$ 630
million.
6. Conclusions
This paper has explored the role of technological
capability accumulation in influencing the differences
between USIMINAS and CSN across different in-
dicators of operational performance improvement.
In sum, the experience of USIMINAS suggests thatif CSN had accumulated technological capability at
similar rates to USIMINAS over the 1940–1980s
period, the company could have achieved faster rates
of performance improvement earlier and caught up
with world competitive levels much more rapidly.
The paper suggests the following conclusions.
1. At least in the steel industry, the long-term accu-
mulation and sustaining of high-level innovative
technological capability (Level 5 and beyond) for
individual technological functions are influenced
by the way and rate at which other types of capa-
bilities are accumulated and sustained over time.
In other words, particularly from Level 5, capabil-
ities become highly interdependent. In addition, it
is unlikely that the latecomer company can move
further towards the technological frontier without
accumulating and sustaining capabilities at the
same high level across a wide number of techno-
18 See BNDES (1994); see also Paula (1998).
logical functions. Therefore, capabilities across all
five technological functions need to be accumu-
lated and sustained in parallel.
2. The evidence also suggests that the accumula-tion of routine operating capability (Levels 1
and 2) plays a critical role in the accumulation
and sustaining of innovative capabilities. For in-
stance, USIMINAS would not have achieved rapid
accumulation of product development capability
if it had not developed and strengthened Levels 1
and 2 routine capability for products and process
and production organisation. Neither would the
company have been able to engage successfully in
the development of ‘capacity-stretching’ capabil-
ity if it had not accumulated Levels 1–4 routine
capability for investments. Indeed, interviews with
managers at different levels in USIMINAS even
recognised the presence of two trajectories of capa-
bility (operating and innovative) running inside the
company. In contrast, in CSN (1940–1980s), the
slow rate and inconsistent way of accumulation
of product development capability was associated
with the incomplete accumulation of routine oper-
ating capability (Levels 1 and 2) for products and
process and production organisation.
3. There is a strong association between rates of
operational performance improvement and the rateof accumulation and the consistency over time of
the paths of technological capability accumula-
tion. Indeed, at least in the steel industry, the fast
improvement of operational performance depends
on the fast accumulation and sustaining of differ-
ent types and levels of ‘routine’ and ‘innovative’
technological capabilities.
4. As analysed in detail elsewhere (Figueiredo, 1999),
the key features of the underlying learning pro-
cesses exert a strong influence on the inter-firm
differences in paths of technological accumula-tion. Thus, if these processes are deliberately and
effectively manipulated over time they produce
positive implications for the accumulation of tech-
nological capability. This, in turn, has positive
implications for the rate of operational performance
improvement and is likely to generate financial
benefits for the company. In other words, continu-
ous and effective in-house efforts on the building,
accumulation and sustaining of different types
and levels of routine and innovative technological
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P.N. Figueiredo / Research Policy 31 (2002) 73–94 93
capabilities—through different learning processes
do pay off.
5. Nevertheless, as argued elsewhere (Figueiredo,
1999), in addition to the learning processes andtechnological capability accumulation, other fac-
tors are also necessary to accelerate the rate of
operational performance improvement: an effec-
tive corporate leadership and a competitive market
environment.
Acknowledgements
I am deeply grateful to Martin Bell at SPRU and
John Bessant at CENTRIM—Centre for Research
in Innovation Management—at the University of
Brighton, UK, for their superb guidance during my
doctorate work. I am also deeply grateful to Keith
Pavitt at SPRU and Sanjaya Lall at the University of
Oxford, UK, for their constructive comments during
the oral examination. Also, I wish to thank the two
anonymous referees for their encouraging comments.
I am tremendously indebted to the two steel compa-
nies for their invaluable co-operation in this study.
Finally, I am indebted to CAPES—the Brazilian
Government Agency for postgraduate support—for
funding for this research.
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